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Elizabeth L. Scott Award Goes to Madhu Mazumdar

May 2, 2022 Leave a Comment

Madhu Mazumdar

The Committee of Presidents of Statistical Societies Elizabeth L. Scott Award committee recently honored Madhu Mazumdar of the Icahn School of Medicine at Mount Sinai with the 2022 award. Mazumdar was selected for serving as an outstanding role model of leadership and creating new leadership opportunities for statisticians, fostering opportunities in statistics and promoting statistical careers for diverse trainees, training and mentoring the next generation of statistical leaders, and excelling in team science research.

Obituaries for April 2021

April 1, 2021 Leave a Comment

ASA members Jim Harner and Allan Sampson passed away recently.

Nandini Kannan

March 1, 2021 1 Comment

Nandini Kannan was born in Bhopal, India, and completed her schooling in Mumbai and New Delhi. She enjoyed solving math puzzles as a child, inheriting her love of mathematics from her father, a mathematician. After completing a master’s degree at the University of Madras, Kannan joined the University of Pittsburgh to work with C. R. Rao. She is proud of her work at the National Science Foundation developing interdisciplinary research and training programs in data science and is passionate about the critical role science and technology play in this global interconnected society. Kannan is committed to developing and supporting initiatives that address diversity and equity in the STEM workforce.

New Graduate Data Science Programs, Continued

December 1, 2019 1 Comment

The proliferation of master’s and doctoral programs in data science and analytics continues. Given their interdisciplinary nature, we identified programs involving faculty with expertise in different disciplines—including statistics—and asked them a few questions.

Lifetime Data Science (LiDS) Is Newest ASA Section

January 3, 2019 Leave a Comment

The ASA Section on Lifetime Data Science (LiDS) is the latest to be voted in by the Council of Sections. The objective of the section is to promote and support the development, application, and appropriate use of statistical methods for the design and analysis of studies of life history processes.

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